Class cv::xfeatures2d::VGG#

Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in [275]. View details

#include <opencv2/xfeatures2d.hpp>

Collaboration diagram for cv::xfeatures2d::VGG:

Public Types#

enum cv::xfeatures2d::VGG {
    cv::xfeatures2d::VGG_120 = 100,
    cv::xfeatures2d::VGG_80 = 101,
    cv::xfeatures2d::VGG_64 = 102,
    cv::xfeatures2d::VGG_48 = 103
}

Public Member Functions#

Public Member Functions inherited from cv::Feature2D

Return	Name	Description
	`~Feature2D()`
`void`	`compute(` `InputArray image,` `std::vector< KeyPoint > & keypoints,` `OutputArray descriptors )`	Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).
`void`	`compute(` `InputArrayOfArrays images,` `std::vector< std::vector< KeyPoint > > & keypoints,` `OutputArrayOfArrays descriptors )`
`int`	`defaultNorm()`
`int`	`descriptorSize()`
`int`	`descriptorType()`
`void`	`detect(` `InputArray image,` `std::vector< KeyPoint > & keypoints,` `InputArray mask = noArray() )`	Detects keypoints in an image (first variant) or image set (second variant).
`void`	`detect(` `InputArrayOfArrays images,` `std::vector< std::vector< KeyPoint > > & keypoints,` `InputArrayOfArrays masks = noArray() )`
`void`	`detectAndCompute(` `InputArray image,` `InputArray mask,` `std::vector< KeyPoint > & keypoints,` `OutputArray descriptors,` `bool useProvidedKeypoints = false )`
`bool`	`empty()`	Return true if detector object is empty.
`String`	`getDefaultName()`
`void`	`read(const FileNode & fn)`	Reads algorithm parameters from a file storage.
`void`	`read(const String & fileName)`
`void`	`write(const String & fileName)`
`void`	`write(FileStorage & fs)`	Stores algorithm parameters in a file storage.
`void`	`write(` `FileStorage & fs,` `const String & name )`

Public Member Functions inherited from cv::Algorithm

Return	Name	Description
	`Algorithm()`
	`~Algorithm()`
`void`	`clear()`	Clears the algorithm state.
`bool`	`empty()`	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
`String`	`getDefaultName()`
`void`	`read(const FileNode & fn)`	Reads algorithm parameters from a file storage.
`void`	`save(const String & filename)`
`void`	`write(` `const Ptr< FileStorage > & fs,` `const String & name = String() )`
`void`	`write(FileStorage & fs)`	Stores algorithm parameters in a file storage.
`void`	`write(` `FileStorage & fs,` `const String & name )`

Static Public Member Functions#

Static Public Member Functions inherited from cv::Algorithm

Return	Name	Description
`static Ptr< _Tp >`	`load(` `const String & filename,` `const String & objname = String() )`	Loads algorithm from the file.
`static Ptr< _Tp >`	`loadFromString(` `const String & strModel,` `const String & objname = String() )`	Loads algorithm from a String.
`static Ptr< _Tp >`	`read(const FileNode & fn)`	Reads algorithm from the file node.

Additional Inherited Members#

Detailed Description#

Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using “Descriptor Learning Using Convex Optimisation” (DLCO) aparatus described in Simonyan14.

Param desc:: type of descriptor to use, VGG::VGG_120 is default (120 dimensions float) Available types are VGG::VGG_120, VGG::VGG_80, VGG::VGG_64, VGG::VGG_48
Param isigma:: gaussian kernel value for image blur (default is 1.4f)
Param img_normalize:: use image sample intensity normalization (enabled by default)
Param use_orientation:: sample patterns using keypoints orientation, enabled by default
Param scale_factor:: adjust the sampling window of detected keypoints to 64.0f (VGG sampling window) 6.25f is default and fits for KAZE, SURF detected keypoints window ratio 6.75f should be the scale for SIFT detected keypoints window ratio 5.00f should be the scale for AKAZE, MSD, AGAST, FAST, BRISK keypoints window ratio 0.75f should be the scale for ORB keypoints ratio
Param dsc_normalize:: clamp descriptors to 255 and convert to uchar CV_8UC1 (disabled by default)

Member Enumeration Documentation#

enum VGG

VGG_120

VGG_80

VGG_64

VGG_48

Member Function Documentation#

create()#

static Ptr< VGG > cv::xfeatures2d::VGG::create(
int desc = VGG::VGG_120,
float isigma = 1.4f,
bool img_normalize = true,
bool use_scale_orientation = true,
float scale_factor = 6.25f,
bool dsc_normalize = false )

getDefaultName()#

String cv::xfeatures2d::VGG::getDefaultName()

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

getScaleFactor()#

float cv::xfeatures2d::VGG::getScaleFactor()

getSigma()#

float cv::xfeatures2d::VGG::getSigma()

getUseNormalizeDescriptor()#

bool cv::xfeatures2d::VGG::getUseNormalizeDescriptor()

getUseNormalizeImage()#

bool cv::xfeatures2d::VGG::getUseNormalizeImage()

getUseScaleOrientation()#

bool cv::xfeatures2d::VGG::getUseScaleOrientation()

setScaleFactor()#

void cv::xfeatures2d::VGG::setScaleFactor(const float scale_factor)

setSigma()#

void cv::xfeatures2d::VGG::setSigma(const float isigma)

setUseNormalizeDescriptor()#

void cv::xfeatures2d::VGG::setUseNormalizeDescriptor(const bool dsc_normalize)

setUseNormalizeImage()#

void cv::xfeatures2d::VGG::setUseNormalizeImage(const bool img_normalize)

setUseScaleOrientation()#

void cv::xfeatures2d::VGG::setUseScaleOrientation(const bool use_scale_orientation)

Source file#

The documentation for this class was generated from the following file:

opencv2/xfeatures2d.hpp